Mapping lightning/human-caused wildfires occurrence under ignition point location uncertainty

Ecological Modelling

Volumn 200, Issue 3-4, 2007, Pages 321-333

  Amatulli, Giuseppe ^a,b,c   Peréz Cabello, Fernando ^a   de la Riva, Juan ^a  

^a UNIVERSITY OF ZARAGOZA   (Spain)

^b UNIVERSITY OF BASILICATA   (Italy)

^c JOINT RESEARCH CENTRE   (Italy)

Author keywords

Fire atlas; Fire ignition points; Fire occurrence; Fire spatial patterns; Kernel density; Location uncertainty

Indexed keywords

BANDWIDTH; DECISION MAKING; GEOGRAPHICAL REGIONS; IGNITION; INTERPOLATION; KNOWLEDGE ACQUISITION; LIGHTNING; MAPPING; MATHEMATICAL MODELS;

FIRE ATLAS; FIRE IGNITION POINTS; FIRE OCCURRENCE; FIRE SPATIAL PATTERNS; KERNEL DENSITY; LOCATION UNCERTAINTY;

FIRES;

FIRE HISTORY; HUMAN ACTIVITY; LIGHTNING; MAPPING METHOD; WILDFIRE;

EID: 33845380313     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2006.08.001     Document Type: Article

References (49)

1. Albers C.J., and Schaafsma W. Estimating a density by adapting an initial guess. Comput. Stat. Data Anal. 42 1-2 (2003) 27-36
2. Allgöwer B., Camia A., Francesetti A., and Koutsias N. Fire hot spot areas in Southern Europe. Detection of large-scale wildland fire occurrence patterns by adaptive kernel density interpolation. In: de la Riva J., Peréz-Cabello F., and Chuvieco E. (Eds). Proceeding of the 5th International Workshop on Remote Sensing and GIS Applications to Forest Fire Management: Fire Effects Assessment (2005) 47-50
3. Amatulli, G., Rodrigues, M.J., Trombetti, M., Lovreglio, R., 2006. Assessing long-term fire risk at local scale by means of decision tree technique. J. Geophys. Res. 111, G04S05, doi:10.1029/2005JG000133.
4. Amatulli G., Rodrigues M.J., Trombetti M., and Lovreglio R. Assessing long-term fire risk at local area by means of decision tree technique; assist fire managers in Decision Support System. In: de la Riva J., Peréz-Cabello F., and Chuvieco E. (Eds). Proceeding of the 5th International Workshop on Remote Sensing and GIS Applications to Forest Fire Management: Fire Effects Assessment (2005) 101-106
5. Bailey T.C., and Gatrell A.C. Interactive spatial data analysis. Longman Scientific & Technical (1995), Burnt Mill, Essex, England 313 pp
6. In: Bowman A.W., and Azzalini A. (Eds). Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations (1997), Oxford University Press, Oxford 193 pp
7. Breiman L., Meisel W., and Purcell E. Variable kernel estimates of multivariate densities. Technometrics 19 (1977) 135-144
8. In: Burt J.E., and Barber G.M. (Eds). Elementary Statistics for Geographers (1996), Guilford Press, New York 513 pp
9. Cochrane M.A., and Laureance W.F. Fire as a large-scale edge effect in Amazonian forests. J. Trop. Ecol. 18 (2002) 311-325
10. Cochrane M.A., and Schulze M.D. Fire as a recurrent event in tropical forests of eastern Amazon: effects on forest structure, biomass and species composition. Biotropica 31 (1999) 2-16
11. Davis J.H., Howe R.W., and Davis G.J. A multi-scale spatial analysis method for point data. Landscape Ecol. 15 (2000) 99-114
12. de Bruin R., Salomé D., and Schaafsma W. A semi-Bayesian method for nonparametric density estimation. Comput. Stat. Data Anal. Arch. 30 1 (1999) 19-30
13. de la Riva J., Pérez-Cabello F., Lana Renault N., and Koutsias N. Mapping forest fire occurrence at a regional scale. Remote Sens. Environ. 92 (2004) 363-369
14. de la Riva, J., Pérez-Cabello, F., 2005. El factor humano en el riesgo de incendios forestales a escala municipal. Aplicación de técnicas SIG para su modelización. In La ciencia forestal: respuestas para la sostenibilidad. 4° Congreso Forestal Español. Sociedad Española de Ciencias Forestales, Madrid, p. 339.
15. de la Riva, J., Pérez-Cabello, F., Chuvieco, E., 2006. Wildland fire ignition danger spatial modelling using GIS and satellite data. In: EGU General Assembly-European Geosciences Union. Geophysical Research Abstracts, 8, 10321.
16. Devroye L., and Lugosi G. Variable kernel estimates: on the impossibility of tuning the parameters. In: Giné E., Mason D., and Wellner J. (Eds). High-Dimensional Probability II (2000), Springer-Verlag, New York 405-424
17. European Commission, Barbosa, P., San-Miguel-Ayanz, J., Camia, A., Gimeno, M., Libertà, G., Schmuck, G., 2004. Special Report: Assessment of fire damages in the EU Mediterranean Countries during the 2003 Forest Fire Campaign, Official Publication of the European Communities, SPI.04.64 EN.
18. In: Fotheringham A.S., Brunsdon C., and Charlton M.E. (Eds). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (2002), Wiley, Chichester 282 pp
19. Gatrell A., Bailey T., Diggle P., and Rowlingson B. Spatial point pattern analysis and its application in geographical epidemiology. Trans. Inst. Br. Geographers 21 (1996) 256-274
20. Gobierno de Aragon, 2000-2003. Plan Cuatrienal de Protección Contra Incendios Forestales en la Comunidad Autónoma de Aragón. Zaragoza, 78 pp.
21. Gutiérrez-Osuna R. Kernel density estimation. CPSC 689-604: Special Topics in Pattern Classification and Clustering (2004), Texas A&M University Computer Science Department
22. Hall P., Sheather S.J., Jones M.C., and Marron J.S. On optimal data-based bandwidth selection in kernel density estimation. Biometrika 78 (1991) 263-269
23. Holdsworth A.R., and Uhl C. Fire in eastern Amazonian logged rain forest and potential for fire reduction. Ecol. Appl. 7 (1997) 713-725
24. Katkovnik V., and Shmulevich I. Kernel density estimation with adaptive varying window size. Pattern Recognit. Lett. 23 (2002) 1641-1648
25. Kelsall J.E., and Diggle P.J. Kernel estimation of relative risk. Bernoulli 1 (1995) 3-16
26. Koutsias N., Kalabokidis K.D., and Allgöwer B. Fire occurrence patterns at landscape level: beyond positional accuracy of ignition points with kernel density estimation methods. Nat. Resour. Modell. 17 4 (2004) 359-376
27. Larjavaara M., Kuuluvainena T., and Ritab H. Spatial distribution of lightning-ignited forest fires in Finland. Forest Ecol. Manage. 208 (2005) 177-188
28. Lasanta T., González-Hidalgo J.C., Vicente-Serrano S.M., and Sferi E. Using landscape ecology to evaluate an alternative management scenario in abandoned Mediterranean mountain areas. Landscape Urban Planning 78 1-2 (2006) 101-114
29. Lasanta T., Vicente-Serrano S., and Cuadrat-Prats J. Mountain Mediterranean landscape evolution caused by the abandonment of traditional primary activities: A study of the Spanish Central Pyrenees. Appl. Geogr. 25 1 (2005) 47-65
30. Leone, V., Koutsias, N., Martínez, J., Vega-García, C., Allgöwer, B., Lovreglio, R., 2003. The human factor in fire danger assessment. In: Chuvieco, E. (Ed.), Wildland Fire Danger Estimation and Mapping: The Role of Remote Sensing Data, World Sci., Hackensack, N.J. pp. 143-196.
31. Levine N. CrimeStat II Computer Program A Spatial Statistics Program for the Analysis of Crime Incident Locations (Version 2.0) (2002), Ned Levine and Associates, Annandale, VA/The National Institute of Justice, Washington, DC
32. Li C. Estimation of fire frequency and fire cycle: a computational perspective. Ecol. Modell. 154 (2002) 103-120
33. Loftsgaarden D., and Quesenberry C. A nonparametric estimate of a multivariate density function. Ann. Math. Stat. 36 (1965) 1049-1051
34. Mapa Forestal de Aragón, 2000. Diputación General de Aragón-Gobierno de Aragón, Zaragoza.
35. Maselli F., Romanelli S., Bottai L., and Zipoli G. Use of NOAA-AVHRR NDVI images for the estimation of dynamic fire risk in Mediterranean areas. Remote Sens. Environ. 86 2 (2003) 187-197
36. Martín M.P., Viedma D., and Chuvieco E. High versus low resolution satellite images to estimate burned areas in large forest fires. In: Viegas D.X. (Ed). Proceeding of 2nd International Conference of Forest Fire Research (1994), ADAI, University of Coimbra, Coimbra, Portugal 653-663
37. Moreno J.M., Vázquez A., and Vélez R. Recent history of forest fires in Spain. In: Moreno J.M. (Ed). Large Forest Fire (1998), Backhuys Publishers, Leiden, The Netherlands 159-185
38. Morgan P., Hardy C.C., Swetnam T.W., Rollins M.G., and Donald G. Mapping fire regimes across time and scale: understanding coarse and fine-scale fire patterns. Int. J. Wildland Fire 10 (2001) 329-342
39. Parzen E. On estimation of a probability density function and mode. Ann. Math. Stat. 33 (1962) 1065-1076
40. Pew K.L., and Larsen C.P.S. GIS analysis of spatial and temporal patterns of human-caused wildfires in the temperate rain forest of Vancouver Island, Canada. Forest Ecol. Manage. 140 (2001) 1-18
41. Podur J., Martell D.L., and Csillag F. Spatial patterns of lightning-caused forest fires in Ontario, 1976-1998. Ecol. Modell. 164 (2003) 1-20
42. Rosenblatt M. Remarks on some nonparametric estimates of a density function. Ann. Math. Stat. 27 (1956) 832-837
43. Seaman D.E., and Powell R.A. An evaluation of the accuracy of kernel density estimators for home range analysis. Ecology 77 (1996) 2075-2085
44. South A.A. Nonparametric spatial rainfall characterization using adaptive kernel estimator. J. Geographic Inf. Decis. Anal. 2 2 (1998) 34-43
45. Telesca L., Amatulli G., Lasaponara R., Lovallo M., and Santulli A. Time-scaling propierties in forest-fire sequences observed in Gargano area (southern Italy). Ecol. Modell. 185 (2005) 531-544
46. Van Kerm P. Adaptive kernel density estimation. Stata J. 3 2 (2003) 148-156
47. Vázquez A., and Moreno J.M. Sensitivity of fire occurrence to meteorological variables in Mediterranean and Atlantic areas of Spain. Landscape Urban Planning 24 1-4 (1993) 129-142
48. Vázquez A., and Moreno J.M. Spatial distribution of forest fires in Sierra de Gredos (Central Spain). Forest Ecol. Manage. 147 1 (2001) 55-65
49. Worton B.J. Kernel methods for estimating the utilization distribution in home-range studies. Ecology 70 (1989) 164-168